QDXray

Because passive networks don’t speak for themselves, observability becomes an analytics problem first — and a monitoring problem second.

Modern access observability relies on:

• Pattern recognition across thousands of alarms
• Behavioral baselining of optical levels and RF metrics
• Spatial clustering of failing endpoints
• Topology-aware correlation
• Time-based degradation detection
• Root-cause inference across shared infrastructure

AI-driven algorithms can:

• Distinguish mass outages from household faults
• Separate optical degradation from power failures
• Infer likely break points in feeder fibers or splitter trees
• Predict failing segments before customers call
• Suppress alarm storms while escalating real incidents

Instead of reacting to single-device alerts, operations teams gain a network-wide understanding of what is really happening in the field.